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Topological Aspects of Dendrimers via Connection-Based Descriptors

Muhammad Javaid1, Ahmed Alamer2, Aqsa Sattar1,*

1 Department of Mathematics, School of Science, University of Management and Technology, Lahore, 54770, Pakistan
2 Department of Mathematics, College of Science, University of Tabuk, Tabuk, 7149, Saudi Arabia

* Corresponding Author: Aqsa Sattar. Email: email

(This article belongs to the Special Issue: Resolvability Parameters and their Applications)

Computer Modeling in Engineering & Sciences 2023, 135(2), 1649-1667. https://doi.org/10.32604/cmes.2022.022832

Abstract

Topological indices (TIs) have been practiced for distinct wide-ranging physicochemical applications, especially used to characterize and model the chemical structures of various molecular compounds such as dendrimers, nanotubes and neural networks with respect to their certain properties such as solubility, chemical stability and low cytotoxicity. Dendrimers are prolonged artificially synthesized or amalgamated natural macromolecules with a sequential layer of branches enclosing a central core. A present-day trend in mathematical and computational chemistry is the characterization of molecular structure by applying topological approaches, including numerical graph invariants. Among topological descriptors, Zagreb connection indices (ZCIs) have much importance. This manuscript involves the establishment of general results to calculate ZCIs, namely first ZCI (FZCI), second ZCI (SZCI), third ZCI (TZCI), modified FZCI, modified SZCI and modified TZCI of two special types of dendrimers nanostars, namely, poly propylene imine octamin (PPIO) dendrimer and poly (propyl) ether imine (PPEtIm) dendrimer. Furthermore, we provide the numerical and graphical comparative analysis of our calculated results for both types of dendrimers with each other.

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Cite This Article

Javaid, M., Alamer, A., Sattar, A. (2023). Topological Aspects of Dendrimers via Connection-Based Descriptors. CMES-Computer Modeling in Engineering & Sciences, 135(2), 1649–1667. https://doi.org/10.32604/cmes.2022.022832



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